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1.
东海初级生产力遥感反演及其时空演化机制 总被引：1，自引：0，他引：1
According to calculation results of ocean chlorophyll concentration based on SeaWiFS data by SeaBAM model and synchronous ship-measured data, this research set up an improved model for Case I and Case Ⅱ water bodies respectively. The monthly chlorophyll distribution in the East China Sea in 1998 was obtained from this improved model on calculation results of SeaBAM. The euphotic depth distribution in 1998 in the East China Sea is calculated by using remote sensing data of K490 from SeaWiFS according to the relation between the euphotic depth and the oceanic diffuse attenuation coefficient. With data of ocean chlorophyll concentration, euphotic depth, ocean surface photosynthetic available radiation (PAR), daily photoperiod and optimal rate of daily carbon fixation within a water column, the monthly and annual primary productivity spatio-temporal distributions in the East China Sea in 1998 were obtained based on VGPM model. Based on analysis of those distributions, the conclusion can be drawn that there is a clear bimodality character of primary productivity in the monthly distribution in the East China Sea. In detail, the monthly distribution of primary productivity stays the lowest level in winter and rises rapidly to the peak in spring. It gets down a little in summer, and gets up a little in autumn. The daily average of primary productivity in the whole East China Sea is 560.03 mg/m^2/d, which is far higher than the average of subtropical ocean areas. The annual average of primary productivity is 236.95 g/m^2/a. The research on the seasonal variety mechanism of primary productivity shows that several factors that affect the spatio-temporal distribution may include the chlorophyll concentration distribution, temperature condition, the Yangtze River diluted water variety, the euphotic depth, ocean current variety, etc. But the main influencing factors may be different in each local sea area. 相似文献
2.
According to calculation results of ocean chlorophyll concentration based on SeaWiFS data by SeaBAM model and synchronous ship-measured data, this research set up an improved model for CaseⅠand CaseⅡwater bodies respectively. The monthly chlorophyll distribution in the East China Sea in 1998 was obtained from this improved model on calculation results of SeaBAM. The euphotic depth distribution in 1998 in the East China Sea is calculated by using remote sensing data of K490 from SeaWiFS according to the relation between the euphotic depth and the oceanic diffuse attenuation coefficient. With data of ocean chlorophyll concentration, euphotic depth, ocean surface photosynthetic available radiation (PAR), daily photoperiod and optimal rate of daily carbon fixation within a water column, the monthly and annual primary productivity spatio-temporal distributions in the East China Sea in 1998 were obtained based on VGPM model. Based on analysis of those distributions, the conclusion can be drawn that there is a clear bimodality character of primary productivity in the monthly distribution in the East China Sea. In detail, the monthly distribution of primary productivity stays the lowest level in winter and rises rapidly to the peak in spring. It gets down a little in summer, and gets up a little in autumn. The daily average of primary productivity in the whole East China Sea is 560.03 mg/m2/d, which is far higher than the average of subtropical ocean areas. The annual average of primary productivity is 236.95 g/m2/a. The research on the seasonal variety mechanism of primary productivity shows that several factors that affect the spatio-temporal distribution may include the chlorophyll concentration distribution, temperature condition, the Yangtze River diluted water variety, the euphotic depth, ocean current variety, etc. But the main influencing factors may be different in each local sea area. 相似文献
3.
1 IntroductionAs a major part of terrestrial ecosystem, vegetation plays an important role in the energy, matter and momentum exchange between land surface and atmosphere. Through the process of photosynthesis, land plants assimilate carbon in atmosphere and incorporate into dry matter while part of carbon is emitted into atmosphere again through plant respiration. The remainder of photosynthesis and respiration is called net primary productivity (NPP), which is important in the global carbon… 相似文献
4.
Current ecosystem models used to simulate global terrestrial carbon balance generally suggest that terrestrial landscapes are stable and mature, but terrestrial net primary productivity(NPP) data estimated without accounting for disturbances in species composition, environment, structure, and ecological characteristics will reduce the accuracy of the global carbon budget. Therefore, the steady-state assumption and neglect of elevation-related changes in forest NPP is a concern. The Qilian Mounta... 相似文献
5.
Wetland ecosystems are crucial to the global carbon cycle.In this study,the Zhalong Wetland was investigated.Based on remote sensing and meteorological observation data from 1975–2018 and the downscaled fifth phase of the coupled model intercomparison project (CMIP5) climate projection dataset from 1961–2100,the parameters of a net primary productivity (NPP) climatic potential productivity model were adjusted,and the simulation ability of the CMIP5 coupled models was evaluated.On this basis,we analysed the spatial and temporal variations of land cover types and landscape transformation processes in the Zhalong Nature Reserve over the past 44 years.We also evaluated the influence of climate change on the NPP of the vegetation,microbial heterotrophic respiration (Rh),and net ecosystem productivity (NEP) of the Zhalong Wetland and predicted the carbon sequestration potential of the Zhalong Wetland from 2019–2029 under the representative concentration pathways (RCP) 4.5 and RCP 8.5 scenarios.Our results indicate the following:(1) Herbaceous bog was the primary land cover type of the Zhalong Nature Reserve,occupying an average area of 1168.02±224.05 km~2,equivalent to 51.84%of the total reserve area.(2)Since 1975,the Zhalong Nature Reserve has undergone a dry–wet–dry transformation process.Excluding several wet periods during the mid-1980s to early 1990s,the reserve has remained a dry habitat,with particularly severe conditions from 2000 onwards.(3) The 1975–2018 mean NPP,Rh,and NEP values of the Zhalong Wetland were 500.21±52.76,337.59±10.80,and 162.62±45.56 g C·m~(-2)·a~(-1),respectively,and an evaluation of the carbon balance indicated that the reserve served as a carbon sink.(4) From 1975–2018,NPP showed a significant linear increase,Rh showed a highly significant linear increase,while the increase in the carbon absorption rate was smaller than the increase in the carbon release rate.(5) Variations in NPP and NEP were precipitation-driven,with the correlations of NPP and NEP with annual precipitation and summer precipitation being highly significantly positive(P0.001);variations in Rh were temperature-driven,with the correlations of Rh with the average annual,summer,and autumn temperatures being highly significantly positive (P0.001).The interaction of precipitation and temperature enhances the impact on NPP,Rh and NEP.(6) Under the RCP 4.5 and RCP 8.5 scenarios,the predicted carbon sequestration by the Zhalong Wetland from 2019–2029 was 2.421 (±0.225)×10~(11) g C·a~(-1) and 2.407 (±0.382)×10~(11) g C·a~(-1),respectively,which were both lower than the mean carbon sequestration during the last 44 years (2.467 (±0.950)×10~(11) g C·a~(-1)).Future climate change may negatively contribute to the carbon sequestration potential of the Zhalong Wetland.The results of the present study are significant for enhancing the abilities of integrated eco-meteorological monitoring,evaluation,and early warning systems for wetlands. 相似文献
6.
ZHAO Rongqin HUANG Xianjin LIU Ying ZHONG Taiyang DING Minglei CHUAI Xiaowei 《地理学报(英文版)》2014,24(1):159-176
Urban carbon footprint reflects the impact and pressure of human activities on ur- ban environment. Based on city level, this paper estimated carbon emissions and carbon footprint of Nanjing city, analyzed urban carbon footprint intensity and carbon cycle pressure and discussed the influencing factors of carbon footprint through LMDI decomposition model. The main conclusions are as follows： （1） The total carbon emissions of Nanjing increased rapidly since 2000, in which the carbon emission from the use of fossil energy was the largest Meanwhile, carbon sinks of Nanjing presented a declining trend since 2000, which caused the decrease of carbon compensation rate and the increase of urban carbon cycle pressure. （2） The total carbon footprint of Nanjing increased rapidly since 2000, and the carbon deficit was more than ten times of total land areas of Nanjing in 2009, which means Nanjing confronted high carbon cycle pressure. （3） Generally, carbon footprint intensity of Nanjing was on de- crease and the carbon footprint productivity was on increase. This indicated that energy utilization rate and carbon efficiency of Nanjing was improved since 2000, and the policy for energy conservation and emission reduction taken by Nanjing＇s government received better effects. （4） Economic development, population and industrial structure are promoting factors for the increase of carbon footprint of Nanjing, while the industrial carbon footprint intensity was inhibitory factor. （5） Several countermeasures should be taken to decrease urban carbon footprint and alleviate carbon cycle pressure, such as： improvement of the energy efficiency, industrial structure reconstruction, afforestation and environmental protection and land use control. Generally, transition to low-carbon economy is essential for Chinese cities to realize sustainable development in the future. 相似文献
7.
生态退耕对中国农田生产力的影响(英文) 总被引：1，自引：0，他引：1
The changes in cropland quantity and quality due to land use are critical concerns to national food security, particularly for China. Despite the significant ecological effects, the ecological restoration program (ERP), started from 1999, has evidently altered the spatial patterns of China’s cropland and agricultural productivity. Based on cropland dynamic data from 2000 to 2008 primarily derived from satellite images with a 30-m resolution and satellite-based net primary productivity models, we identified the impacts on agricultural productivity caused by ERP, including "Grain for Green" Program (GFGP) and "Reclaimed Cropland to Lake" (RCTL) Program. Our results indicated that the agricultural productivity lost with a rate of 132.67×104 t/a due to ERP, which accounted for 44.01% of the total loss rate caused by land use changes during 2000-2005. During 2005-2008, the loss rate due to ERP decreased to 77.18×104 t/a, which was equivalent to 58.17% of that in the first five years and 30.22% of the total loss rate caused by land use changes. The agricultural productivity loss from 2000-2008 caused by ERP was more attributed to GFGP (about 70%) than RCTL. Although ERP had a certain influence on cropland productivity during 2000-2008, its effect was still much less than that of urbanization; moreover, ERP was already converted from the project implementation phase to the consolidation phase. 相似文献
8.
Land-use and soil management affects soil organic carbon （SOC） pools, nitrogen, salinity and the depth distribution. The objective of this study was to estimate land-use effects on the distribution of SOC, labile fractions C, nitrogen （N） and salinity in saline-alkaline wetlands in the middle reaches of the Heihe River Basin. Three land-use types were selected： intact saline-alkaline meadow wetland, artificial shrubbery （planting Tamarix） and farmland （cultivated for 18 years） of soils previously under meadow wetland. SOC, easily oxidized carbon, microbial biomass carbon, total N, NO3--N and salinity concentrations were measured. The results show that SOC and labile fraction carbon contents decreased significantly with increasing soil depth in the three land-use wetlands. The labile fraction carbon contents in the topsoil （0-20cm） in cultivated soils were significantly higher than that in intact meadow wetland and artificial shrubbery soil. The aboveground biomass and soil permeability were the primary influencing factors on the contents of SOC and the labile carbon in the intact meadow wetland and artificial shrubbery soil, however, the farming practice was a factor in cultivated soil. Agricultural measures can effectively reduce the salinity contents; however, it caused a significant increase of NO 3--N concentrations which posed a threat to groundwater quality in the study area. 相似文献
9.
The leaf area index(LAI) shows a significant increasing trend from global to regional scales, which is known as greening. Greening will further enhance photosynthesis, but it is unclear whether the contribution of greening has exceeded the CO2 fertilization effect and become the dominant factor in the gross primary productivity(GPP) variation. We took the Yangtze River Delta(YRD) of China, where cropland and natural vegetation are significantly greening, as an example. Based on the bo... 相似文献
10.
The content and distribution of biogenic silica were investigated in sedi- ment cores from Prydz Bay,Antarctica,during the CHINARE-18/21.cruise.The re- sults show that the content of biogenic silica(BSiO_2) is ranged from 4.89% to 85. 41%,and the average content of biogenic silica is 30.90%,the highest value oc- curred at theⅣ-10 station.The profile of BSiO_2 in sediment is contrast to that of sili- cate in the interstitial water.The content of biogenic silica and organic carbon in the surface sediments in the central area of Prydz Bay gyre were much higher than those in other area,and closely related to the Chla content and primary productivity of phyto- plankton in the surface water column. 相似文献
11.
The spatial and temporal variability of primary productivity in the China seas from 2003 to 2005 was estimated using a size-fractionated primary productivity model. Primary productivity estimated from satellite-derived data showed spatial and temporal variability. Annual averaged primary productivity levels were 564.39, 363.08, 536.47, 413.88, 195.77, and 100.09 gCm-2a-1 in the Bohai Sea, northern Yellow Sea (YS), southern YS, northern East China Sea (ECS), southern ECS, and South China Sea (SCS), respectively. Peaks of primary productivity appeared in spring (April–June) and fall (October and November) in the northern YS, southern YS, and southern ECS, while a single peak (June) appeared in the Bohai Sea and northern ECS. The SCS had two peaks in primary productivity, but these peaks occurred in winter (January) and summer (August), with the winter peak far higher than the summer peak. Monthly averaged primary productivity values from 2003 to 2005 in the Bohai Sea and southern YS were higher than those in the other four seas during most months, while those in the southern ECS and SCS were the lowest. Primary productivity in spring (March–June in the southern ECS and April–July in the other five areas) contributed approximately 41% on average to the annual primary productivity in all the study seas except the SCS. The largest interannual variability also occurred in spring (average standard deviation = 6.68), according to the satellite-derived estimates. The contribution during fall (October–January in the southern ECS and August–November in the other five areas) was approximately 33% on average; the primary productivity during this period also showed interannual variability. However, in the SCS, the winter (December–March) contribution was the highest (about 42%), while the spring (April–July) contribution was the lowest (28%). The SCS did share a feature with the other five areas: the larger the contribution, the larger the interannual variability. Spatial and temporal variability of satellite-derived ocean primary productivity may be influenced by physicochemical environmental conditions, such as the chlorophyll-a concentration, sea surface temperature, photosynthetically available radiation, the seasonally reversed monsoon, river discharge, upwelling, and the Kuroshio and coastal currents. 相似文献
12.
中国近海初级生产力的遥感研究及其时空演化 总被引：3，自引：0，他引：3
利用分级初级生产力模式反演估算了2003~2005年0o~41oN,105o~130oE海域的初级生产力,并分析了它们的时空演化。同时还计算了该时段内渤海、北黄海和南黄海、东海北部和南部以及南海的平均初级生产力状况,结果得出它们的年平均初级生产力 (2003~2005年) 分别为564.39、363.08、536.47、413.88、195.77和100.09 gCm-2a-1。北黄海、南黄海及东海南部的初级生产力分别在春季 (4~6月) 和秋季 (10、11月) 出现两次峰值,且春季的峰值高于秋季。然而,南海的两个峰值则分别出现在冬季 (1月)和夏季 (8月),且冬季的峰值高于夏季。渤海和东海北部则呈现单峰 (6月) 分布。渤海和南黄海的初级生产力几乎在整年内都高于其它海域,而东海南部和南海的初级生产力则在整年内都低于其他海域。其中,南海的初级生产力最低,月平均全都低于400 mgCm-2d-1。除南海以外的其它5个海域,在春季时期 (东海南部为3~6月,其他海域为4~7月) 的初级生产力最高,平均约占年平均值的41%,其年际变化也最大,平均标准偏差为6.68;而秋季时期 (东海南部为10~1月,其他海域为8~11月) 对年平均的贡献也很大,平均约33%;其他月份 (东海南部为2月和7-9月,其他海域为12~3月) 的贡献则最小。南海的初级生产力则在冬季时期 (12~3月) 最高,约占年平均的42%,夏末秋季 (8~11月) 次之,约30%,春季时期 (4~7月) 最低。叶绿素-a、海表温度、光合有效辐射、季风活动、河流排放、上升流、黑潮以及沿岸流等物理-化学环境因子是造成中国近海初级生产力时空演化的主要原因。 相似文献
13.
Based on sediment and discharge flux data for the Yellow River, realistic forcing fields and bathymetry of the Bohai Sea,
a suspended sediment transport module is driven by a wave-current coupled model to research seasonal variations and mechanisms
of suspended load transport to the Bohai Sea. It could be concluded that surface sediment concentration indicates a distinct
spatial distribution characteristic that varies seasonally in the Bohai Sea. Sediment concentration is rather high near the
Yellow River estuary, seasonal variations of which are controlled by quantity of sediment from the Yellow River, suspended
sediment concentration reaches its maximum during summer and fall. Furthermore, sediment concentration decreases rapidly in
other seas far from the Yellow River estuary and maintains a very low level in the center of the Bohai Sea, and is dominated
by seasonal variations of climatology wind field in the Bohai Sea. Only a small amount of sediments imported from the Yellow
River are delivered northwestward to the southern coast of the Bohai Bay. Majority of sediments are transported southeastward
to the Laizhou Bay, where sediments are continuously delivered into the center of the Bohai Sea in a northeastward direction,
and part of them are transported eastward alongshore through the Bohai Strait. 69% of sediments from the Yellow River are
deposited near the river delta, 31% conveyed seaward, within which, 4% exported to the northern Yellow Sea through the Bohai
Strait. Wind wave is the most essential contributor to seasonal variations of sediment concentration in the Bohai Sea, and
the contribution of tidal currents is also significant in shallow waters when wind speed is low. 相似文献
14.
Based on sediment and discharge flux data for the Yellow River, realistic forcing fields and bathymetry of the Bohai Sea, a suspended sediment transport module is driven by a wave-current coupled model to research seasonal variations and mechanisms of suspended load transport to the Bohai Sea. It could be concluded that surface sediment concentration indicates a distinct spatial distribution characteristic that varies seasonally in the Bohai Sea. Sediment concentration is rather high near the Yellow River estuary, seasonal variations of which are controlled by quantity of sediment from the Yellow River, suspended sediment concentration reaches its maximum during summer and fall. Furthermore, sediment concentration decreases rapidly in other seas far from the Yellow River estuary and maintains a very low level in the center of the Bohai Sea, and is dominated by seasonal variations of climatology wind field in the Bohai Sea. Only a small amount of sediments imported from the Yellow River are delivered northwestward to the southern coast of the Bohai Bay. Majority of sediments are transported southeastward to the Laizhou Bay, where sediments are continuously delivered into the center of the Bohai Sea in a northeastward direction, and part of them are transported eastward alongshore through the Bohai Strait. 69% of sediments from the Yellow River are deposited near the river delta, 31% conveyed seaward, within which, 4% exported to the northern Yellow Sea through the Bohai Strait. Wind wave is the most essential contributor to seasonal variations of sediment concentration in the Bohai Sea, and the contribution of tidal currents is also significant in shallow waters when wind speed is low. 相似文献
15.
Liang Liang 《自然地理学》2013,34(6):489-509
Geographic variations in plant phenology are known to be affected by climatic differences over space, but the role of adaptation variability of plant populations is less well understood. In this study, I examined the geographic variations in spring and autumn phenology of white ash (Fraxinus americana L.) in a common garden and related observations over a 2-year period (2013 and 2014) to climatic and geographic factors of their provenances. Spring leaf-out of trees with northern provenances occurred later in 2013, but slightly earlier in 2014, than those with southern provenances. This difference was potentially caused by the counterbalancing effect of chilling and forcing in response to interannual temperature fluctuations. In both years, leaf senescence of white ash occurred significantly earlier for trees with northern than southern provenances, reflecting strong adaptation to a photoperiod gradient. The growing season length for white ash, therefore, is constrained by spring and fall phenology through different environmental cues. Spring phenology exerted a greater influence on the interannual variability of growing season length. Identifying these detailed adaptive patterns facilitates a better understanding of phenological change over space and allows development of genotype-sensitive phenological models to predict the ecological impact of climate change. 相似文献
16.
Genrich V. Alekseev Ola M. Johannessen Alexander A. Korablev Vladimir V. Ivanov Dmitry V. Kovalevsky 《Polar research》2001,20(2):201-208
Oceanographic data covering the period 1950–1998 are used to determine interannual variations in the convection intensity and water mass structure in the Greenland Sea and adjacent areas. Extremely cold winters throughout 1965–1970 assisted intensification of the water vertical exchange in the Greenland and Norwegian seas. As a result, cold and fresh Greenland Sea Deep Water (GSDW) production was extremely high in the central Greenland Sea while in the southern Norwegian Sea warm and salty water spread downwards. The recent rapid warming in the Greenland Sea Gyre interior from 1980 originates, we argue, from an increase in the Atlantic Water (AW) temperature due to the advection of warm waters into the region with the Return Atlantic Current. The negative water temperature and salinity trends in the upper 300 m layer of the Atlantic Water in the Norwegian Sea prevailed during 1950–1990, whereas during 1980–1990 the water temperature trends are indicative of warming of that layer. Observation series obtained onboard the Ocean Weather Ship Mike confirmed the existence of layers with advectiondriven high oxygen concentrations in intermediate and deep layers. The depth of oxygen maxima and the values of oceanographic parameters at this horizon can be regarded as indicators of the convection intensity in the Arctic domain. A simultaneous rise in NAO index and GSDW temperature points to a link between atmospheric and thermohaline circulation. Weakening in water exchange with the North Atlantic could be the reason for the Polar Water recirculation increase within the Nordic seas. 相似文献
17.
中国雾区的分布及其季节变化 总被引：1，自引：0，他引：1
1 Introduction Fog is a weather phenomenon that horizontal visible distance is reduced within 1 km by plenty of water drops and particles of ice crystal. It not only has unfavorable influence on the traffic of water, land and air, but also brings serious … 相似文献
18.
青藏高原近40年来的降水变化特征 总被引：21，自引：7，他引：21
利用我国青藏高原地区的1961-2000年56个气象站的逐月降水资料,通过计算降水量的距平百分率,分析了青藏高原自1961至2000年以来降水量变化的趋势和1961-2000年以来各季降水量变化趋势,发现:青藏高原近40年来降水量呈增加趋势,降水量的线性增长率约为1.12mm/a。再将高原划分为四个季节,分析了各季40年来的降水量的变化情况得出:春季降水量年际变化较大,秋季降水量变化不明显。夏季降水量值较大而降水变化幅度较小,冬季降水量变化则与夏季相反。通过将青藏高原分为南北两个地区,分析了两个区的年降水量和四个季节的降水量的变化得出:高原南区1961-2000年降水量呈增加的趋势,降水量的线增长率为1.97 mm/a,春季和冬季降水量年际变化较大,夏季降水量变化不明显,秋季降水量略有增加;北区年降水量和夏季的降水量变化较小,秋季降水量的年际变化较大,冬季降水量变化最大。对青藏高原的南北两区用Mann-Kendall方法进行突变分析,显示高原南区分别在1978年和1994年发生突变,北区没有发现突变。 相似文献
19.
滨珊瑚（Porites）是南海造礁石珊瑚群落的主要优势种之一,广泛应用于珊瑚礁生态以及高分辨率气候环境响应和重建研究。滨珊瑚不同季节生长形成的骨骼密度条带是开展相关研究的重要基础,而前人对于滨珊瑚骨骼密度带季节性的认识多是基于单一地点的样品,存在地域的差别或矛盾。选取南海不同地点典型珊瑚礁区包括北部海南文昌、中部西沙群岛永兴岛和盘石屿、南部南沙群岛美济礁的 4 个现代活体滨珊瑚骨骼样品,利用数字影像分析方法以及电感耦合等离子体原子发射光谱和气体稳定同位素比质谱仪分别分析了滨珊瑚骨骼密度条带影像灰度和地化指标（Sr/Ca 和 δ 18 O）。结果显示,滨珊瑚样品骨骼密度和地化指标都呈现显著的季节变化。结合海温数据,揭示出样品骨骼密度带季节特征的地域差异,其中,北部文昌滨珊瑚样品骨骼高密度带形成于夏季,低密度带形成于冬季;中部永兴岛样品高密度带形成于秋季,低密度带形成于春季;盘石屿样品高密度带形成于春季,低密度带形成于秋季;南部美济礁样品高密度带形成于冬季,低密度带形成于夏季。采用广义加性混合模型进一步分析了滨珊瑚样品骨骼密度与 3 个主要环境影响因子（海温、光照和盐度）的响应关系。结果表明：不同地点滨珊瑚样品的骨骼密度与主要环境因子的关系也各有不同,考虑样品个体和地点的随机效应,4 个地点滨珊瑚样品的骨骼密度整体上与海温和光照存在非线性响应关系,反映了在南海大空间尺度上,海温和光照可能是影响滨珊瑚样品骨骼密度季节变化的主要环境因素。 相似文献